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At least 91 records · Page 5

Discovery of intrinsic linear polarization in SS433

Observations of variable linear polarization in the optical range in the unique radio and X-ray source SS 433, which is characterized by moving emission lines in its visible and near-IR spectra, are reported. The observations were made with an unfiltered GaAs photocathode covering the spectral region 3000-9000 A, with a passband characteristic wavelength near 7000 A. Measurements reveal the presence of both a long-term and a very short time-scale variation in linear polarization in the continuum and in H-alpha, which indicate that a substantial fraction of the polarization is intrinsic to SS 433 and not produced in the interstellar medium. It is suggested that the most likely source of polarization in the optical continuum is electron scattering, and constraints on models of SS 433 implied by the discovery of intrinsic polarization are considered.

Mclean, I. S.↗

New Candidate Extreme T Subdwarfs from the Backyard Worlds: Planet 9 Citizen Science Project

Schneider et al. presented the discovery of WISEA J041451.67−585456.7 and WISEA J181006.18−101000.5, which appear to be the first examples of extreme T-type subdwarfs (esdTs; metallicity ≤−1 dex, T(eff) ≲ 1400 K). Here, we present new discoveries and follow-up of three T-type subdwarf candidates, with an eye toward expanding the sample of such objects with very low metallicity and extraordinarily high kinematics, properties that suggest membership in the Galactic halo. Keck/NIRES near-infrared spectroscopy of WISEA J155349.96+693355.2, a fast-moving object discovered by the Backyard Worlds: Planet 9 citizen science project, confirms that it is a mid-T subdwarf. With H(W2) = 22.3 mag, WISEA J155349.96+693355.2 has the largest W2 reduced proper motion among all spectroscopically confirmed L and T subdwarfs, suggesting that it may be kinematically extreme. Nevertheless, our modeling of the WISEA J155349.96+693355.2 near-infrared spectrum indicates that its metallicity is only mildly subsolar. In analyzing the J155349.96+693355.2 spectrum, we present a new grid of low-temperature, low-metallicity model atmosphere spectra. We also present the discoveries of two new esdT candidates, CWISE J073844.52−664334.6 and CWISE J221706.28−145437.6, based on their large motions and colors similar to those of the two known esdT objects. Finding more esdT examples is a critical step toward mapping out the spectral sequence and observational properties of this newly identified population.

Aaron M. Meisner↗

LDEF contributions to cosmic ray and radiation environments research

LDEF-1 carried three experiments which are producing significant advances in our knowledge of ultra heavy and anomalous cosmic rays, solar flare particles, and heavy nuclei in the trapped belts. Nine other experiments made measurements on the radiation environments or performed dosmetric monitoring. Data from those experiments, and from measurements of induced radioactivity in LDEF components have significantly improved our knowledge of LEO radiation environment. Measurements at various locations shielding depths of radiation absorbed dose, linear energy transfer spectra, proton, neutron and heavy ion fluences, and induced radioactivity have been made, and many of these results have been compared to models. This has allowed the assessment of accuracy, and the potential for improvement, of the models. Serendipitous results from the radiation measurements include the discovery of atmospheric Be-7 plated on the front surface of LDEF, which has motivated a series of new investigations. A sample of measurements and modeling results will be presented, as well as the status of archiving the measurements and models.

Parnell, Thomas A.↗

High Gain Antenna System Deployment Mechanism Integration, Characterization, and Lessons Learned

The integration and deployment testing of the High Gain Antenna System for the Global Precipitation Measurement mission is summarized. The HGAS deployment mechanism is described. The gravity negation system configuration and its influence on vertical, ground-based, deployment tests are presented with test data and model predictions. A focus is made on the late discovery and resolution of a potentially mission degrading deployment interference condition. The interaction of the flight deployment mechanism, gravity negation mechanism, and use of dynamic modeling is described and lessons learned presented.

000000↗

High Gain Antenna System Deployment Mechanism Integration, Characterization, and Lessons Learned

The integration and deployment testing of the High Gain Antenna System (HGAS) for the Global Precipitation Measurement mission is summarized. The HGAS deployment mechanism is described. The gravity negation system configuration and its influence on vertical, ground-based deployment tests are presented with test data and model predictions. A focus is made on the late discovery and resolution of a potentially mission-degrading deployment interference condition. The interaction of the flight deployment mechanism, gravity-negation mechanism, and use of dynamic modeling is described and lessons learned presented

Parong, Fil↗

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗

An application of miniscale experiments on Earth to refine microgravity analysis of adiabatic multiphase flow in space

Adiabatic two-phase flow is of interest to the design of multiphase fluid and thermal management systems for spacecraft. This paper presents original data and unifies existing data for capillary tubes as a step toward assessing existing multiphase flow analysis and engineering software. Comparisons of theory with these data once again confirm the broad accuracy of the theory. Due to the simplicity and low cost of the capillary tube experiments, which were performed on earth, we were able to closely examine for the first time a flow situation that had not previously been examined appreciably by aircraft tests. This is the situation of a slug flow at high quality, near transition to annular flow. Our comparison of software calculations with these data revealed overprediction of pipeline pressure drop by up to a factor of three. In turn, this finding motivated a reexamination of the existing theory, and then development of a new analytical and is in far better agreement with the data. This sequence of discovery illustrates the role of inexpensive miniscale modeling on earth to anticipate microgravity behavior in space and to complete and help define needs for aircraft tests.

Rothe, Paul H.↗

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗

Modeling Phase-Aligned Gamma-Ray and Radio Millisecond Pulsar Light Curves

Since the discovery of the first eight gamma-ray millisecond pulsars (MSPs) by the Fermi Large Area Telescope, this population has been steadily expanding. Four of the more recent detections, PSR J00340534, PSR J1939+2134 (B1937+21; the first MSP ever discovered), PSR J1959+2048 (B1957+20; the first discovery of a black widow system), and PSR J2214+3000, exhibit a phenomenon not present in the original discoveries: nearly phase-aligned radio and gamma-ray light curves (LCs). To account for the phase alignment, we explore models where both the radio and gamma-ray emission originate either in the outer magnetosphere near the light cylinder or near the polar caps. Using a Markov Chain Monte Carlo technique to search for best-fit model parameters, we obtain reasonable LC fits for the first three of these MSPs in the context of altitude-limited outer gap (alOG) and two-pole caustic (alTPC) geometries (for both gamma-ray and radio emission). These models differ from the standard outer gap (OG)/two-pole caustic (TPC) models in two respects: the radio emission originates in caustics at relatively high altitudes compared to the usual conal radio beams, and we allow both the minimum and maximum altitudes of the gamma-ray and radio emission regions to vary within a limited range (excluding the minimum gamma-ray altitude of the alTPC model, which is kept constant at the stellar radius, and that of the alOG model, which is set to the position-dependent null charge surface altitude). Alternatively, phase-aligned solutions also exist for emission originating near the stellar surface in a slot gap scenario (low-altitude slot gap (laSG) models). We find that the alTPC models provide slightly better LC fits than the alOG models, and both of these give better fits than the laSG models (for the limited range of parameters considered in the case of the laSG models). Thus, our fits imply that the phase-aligned LCs are likely of caustic origin, produced in the outer magnetosphere, and that the radio emission for these pulsars may come from close to the light cylinder. In addition, we were able to constrain the minimum and maximum emission altitudes with typical uncertainties of 30% of the light cylinder radius. Our results therefore describe a third gamma-ray MSP subclass, in addition to the two previously found by Venter et al.: those with LCs fit by standard OG/TPC models and those with LCs fit by pair-starved polar cap models.

Venter, C.↗

The origin and evolution of model organisms

The phylogeny and timescale of life are becoming better understood as the analysis of genomic data from model organisms continues to grow. As a result, discoveries are being made about the early history of life and the origin and development of complex multicellular life. This emerging comparative framework and the emphasis on historical patterns is helping to bridge barriers among organism-based research communities.

Review, Academic↗

Anomaly Detection in Flight Operational Data Using Deep Learning

In this session, we demonstrate two recently developed deep learning models for anomaly detection in flight operational data by the Data Sciences Group at NASA Ames Research Center. The first model is Convolutional Variational Auto-Encoder (CVAE) [1], which is an unsupervised deep encoder-decoder model, designed specifically for finding anomalies in heterogeneous multivariate time series data. We will demonstrate its application to finding anomalies in streaming data from NASA’s Digital Information Platform’s Fuser source. CVAE identifies data instances that are not representative of expected nominal behavior as anomalous. Since it is an unsupervised approach, the flagged anomalies will need to be reviewed by the subject matter experts (SMEs) for validation and labeling and is designed to assist with vulnerability discovery within Safety Monitoring System programs. The second model is Robust and Explainable Semi-supervised Anomaly Detection (RESAD) model [2], which builds on CVAE to allow learning from both minimally labeled data (previously reviewed by the SMEs) as well as majority unlabeled data. RESAD takes advantage of graph theoretic techniques to propagate the labels from the labeled data to the unlabeled data based on a pre-defined similarity metric and structures the learned feature space from flight time-series so that data of the same class would cluster tightly together. This model characteristic is enabled by training with an augmented loss function and allows learning of a more informative feature space for down-stream tasks such as search and active learning. We demonstrate RESAD using data from the NASA DASHlink project [3].

anomaly detection↗

Airborne Astronomy Program

Our understanding about the inter-relationship between the collapsing cloud envelope and the disk has been greatly altered. While the dominant star formation models invoke free fall collapse and r(sup -1.5) density profile, other star formation models are possible. These models invoke either different cloud starting conditions or the mediating effects of magnetic fields to alter the cloud geometry during collapse. To test these models, it is necessary to understand the envelope's physical structure. The discovery of disks, based on millimeter observations around young stellar objects, however makes a simple interpretation of the emission complicated. Depending on the wavelength, the disk or the envelope could dominate emission from a star. In addition, the discovery of planets around other stars has made understanding the disks in their own right quite important. Many star formation models predict disks should form naturally as the star is forming. In many cases, the information we derive about disk properties depends implicitly on the assumed envelope properties. How to understand the two components and their interaction with each other is a key problem of current star formation.

Butner, Harold M.↗

In-Situ Scanning Electron Microscope Experiments for Microscale Mechanical Testing and Validated Modeling of Fiber Reinforced Thermoplastics

A novel, in-situ, scanning electron microscope (SEM) mechanical testing capability for materials at the microscale which provides experimental validation to a machine learning (ML) toolset for full-field validation of physics-based micromechanics models is being developed by researchers at NASA Glenn Research Center. These are enabling technologies for the integration of multiscale digital twins for materials into system level models which will result in the improved performance, material discovery, reduced production cost and time, rapid characterization, and prognostic structural health monitoring (SHM) for materials and structures for extreme environments in support of NASA space exploration missions. In order to bridge the material structure-to-system gap for digital twins, physics-based models must be experimentally validated at multiple length scales. Seminal microscale experiments, conducted at the Air Force Research Laboratory (AFRL), were limited to transverse compression of single-layer, unidirectional thermoset polymer matrix composite (PMC) micropillar specimens [1]. The early phases of the current project followed those initial results and setup to reproduce the compression testing of PMC material on the custom-built piezoelectric actuated micromechanical testing rig built by MicroTesting Solutions LLC. In this work, samples of thermoplastic PMC material were first machined into 3 mm cubes, and then further machining and final milling was done using a Focused Ion Beam (FIB). The initial experiment was done on a pillar roughly 20 µm x 20 µm x 40 µm tall. Additional pillars were milled with final sizes ranging from 20 µm x 20 µm x 40 µm tall to 40 µm x 40 µm x 65 µm tall. A speckle pattern for in-situ full-field measurements using Digital Image Correlation (DIC) was applied with platinum, which was coated on the surface, and then the FIB was used to mill away some of the coating to produce an irregular pattern of Pt on the pillar surface. The samples were loaded into the custom testing rig and placed into the SEM and loaded under compression until failure. Images were collected in the SEM during testing. Post-processing of the images was conducted using DIC to obtain full-field displacement and strain measurements elucidating the role of the matrix as well as fiber-fiber interaction at the microscale within the composite subjected to compression loading well into the non-linear regime of the material. Moreover, the evolution of fiber-matrix debonding and matrix cracking is observed in-situ at the microscale. This data, along with images segmented with a newly developed ML toolset [2], was used to create and validate physics-based micromechanics models. An image of the failed micropillar is shown in Figure 1. The techniques developed in the initial compression experiment was tailored to the validation needs of the models and expanded to include different sized samples as well as possibly tension and fatigue.

Laura Wilson↗

Meteorites, Microfossils and Exobiology

The discovery of evidence for biogenic activity and possible microfossils in a Martian meteorite may have initiated a paradigm shift regarding the existence of extraterrestrial microbial life. Terrestrial extremophiles that live in deep granite and hydrothermal vents and nanofossils in volcanic tuffs have altered the premise that microbial life and microfossils are inconsistent with volcanic activity and igneous rocks. Evidence for biogenic activity and microfossils in meteorites can no longer be dismissed solely because the meteoritic rock matrix is not sedimentary. Meteorite impact-ejection and comets provide mechanisms for planetary cross-contamination of biogenic chemicals, microfossils, and living microorganisms. Hence, previously dismissed evidence for complex indigenous biochemicals and possible microfossils in carbonaceous chondrites must be re-examined. Many similar, unidentifiable, biological-like microstructures have been found in different carbonaceous chondrites and the prevailing terrestrial contaminant model is considered suspect. This paper reports the discovery of microfossils indigenous to the Murchison meteorite. These forms were found in-situ in freshly broken, interior surfaces of the meteorite. Environmental Scanning Electron Microscope (ESEM) and optical microscopy images indicate that a population of different biological-like forms are represented. Energy Dispersive Spectroscopy reveals these forms have high carbon content overlaying an elemental distribution similar to the matrix. Efforts at identification with terrestrial microfossils and microorganisms were negative. Some forms strongly resemble bodies previously isolated in the Orgueil meteorite and considered microfossils by prior researchers. The Murchison forms are interpreted to represent an indigenous population of the preserved and altered carbonized remains (microfossils) of microorganisms that lived in the parent body of this meteorite at diverse times during the past 4.5 billion years (Gy).

Hoover, Richard B.↗

HYTHIRM Radiance Modeling and Image Analyses in Support of STS-119, STS-125 and STS-128 Space Shuttle Hypersonic Re-entries

We provide the first geometrically accurate (i.e., 3-D) temperature maps of the entire windward surface of the Space Shuttle during hypersonic reentry. To accomplish this task we began with estimated surface temperatures derived from CFD models at integral high Mach numbers and used them, the Shuttle's surface properties and reasonable estimates of the sensor-to-target geometry to predict the emitted spectral radiance from the surface (in units of W sr-1 m-2 nm-1). These data were converted to sensor counts using properties of the sensor (e.g. aperture, spectral band, and various efficiencies), the expected background, and the atmosphere transmission to inform the optimal settings for the near-infrared and midwave IR cameras on the Cast Glance aircraft. Once these data were collected, calibrated, edited, registered and co-added we formed both 2-D maps of the scene in the above units and 3-D maps of the bottom surface in temperature that could be compared with not only the initial inputs but also thermocouple data from the Shuttle itself. The 3-D temperature mapping process was based on the initial radiance modeling process. Here temperatures were guessed for each node in a well-resolved 3-D framework, a radiance model was produced and compared to the processed imagery, and corrections to the temperature were estimated until the iterative process converged. This process did very well in characterizing the temperature structure of the large asymmetric boundary layer transition the covered much of the starboard bottom surface of STS-119 Discovery. Both internally estimated accuracies and differences with CFD models and thermocouple measurements are at most a few percent. The technique did less well characterizing the temperature structure of the turbulent wedge behind the trip due to limitations in understanding the true sensor resolution. (Note: Those less inclined to read the entire paper are encouraged to read an Executive Summary provided at the end.)

Gibson, David M.↗

Non-LTE model atmosphere analysis of Nova Cygni 1992

We use spherically symmetric non-local thermodynamic equilibrium (non-LTE), line-blanketed, expanding model atmospheres to analyze the International Ultraviolet Explorer (IUE) and optical spectra of Nova Cygni 1992 during the early phases of its outburst. We find that the first IUE spectrum obtained just after discovery on 1992 February 20, is best reproduced by a model atmosphere with a steep density gradient and homologous expansion, whereas the IUE and optical spectra obtained on February 24 show an extended, optically thick, wind structure. Therefore, we distinguish two phases of the early evolution of the nova photosphere: the initial, rapid, 'fireball' phase and the subsequent, much longer, optically thick 'wind' phase. The importance of line-blanketing in nova spectra is demonstrated. Our preliminary abundance analysis implies that hydrogen is depeleted in the ejecta, corresponding to abundance enhancements of Fe by a factor of approximately 2 and of CNO by more than a factor of 10 when compared to solar abundances. The synthetic spectra reproduce both the observed pseudo-continua as well as most of the observed features from the UV to the optical spectral range and demonstrate the importance of obtaining nearly simultaneous UV and optical spectra for performing accurate analyses of expanding stellar atmospheres (for both novae and supernovae).

Hauschildt, P. H.↗

Direct Imaging of a Cold Jovian Exoplanet in Orbit around the Sun-Like Star GJ 504

Several exoplanets have recently been imaged at wide separations of >10 AU from their parent stars. These span a limited range of ages (<50 Myr) and atmospheric properties, with temperatures of 800-1800 K and very red colors (J −H > 0.5 mag), implying thick cloud covers. Furthermore, substantial model uncertainties exist at these young ages due to the unknown initial conditions at formation, which can lead to an order of magnitude of uncertainty in the modeled planet mass. Here, we report the direct imaging discovery of a Jovian exoplanet around the Sun-like star GJ 504, detected as part of the SEEDS survey. The system is older than all other known directly-imaged planets; as a result, its estimated mass remains in the planetary regime independent of uncertainties related to choices of initial conditions in the exoplanet modeling. Using the most common exoplanet cooling model, and given the system age of 160(+350/−60) Myr, GJ 504 b has an estimated mass of 4(+4.5/−1.0) Jupiter masses, among the lowest of directly imaged planets. Its projected separation of 43.5 AU exceeds the typical outer boundary of approx.. 30 AU predicted for the core accretion mechanism. GJ 504 b is also significantly cooler (510(+30/−20) K)) and has a bluer color (J − H = −0.23 mag) than previously imaged exoplanets, suggesting a largely cloud-free atmosphere accessible to spectroscopic characterization. Thus, it has the potential of providing novel insights into the origins of giant planets, as well as their atmospheric properties.

exoplanets↗

Space Weather Modeling and Prediction for Intermediate Time-scales

Much of solar activity within a sunspot cycle occurs as bursts, or 'seasons' of strong activity over several months, separated by periods of much less activity. The most important space weather effects occur during these bursts. Previous modeling and forecasting efforts have focused on time-scales of hours-to-days and decades-to-centuries. The recent discovery of Rossby waves in the Sun, together with recently developed global models of solar MHD Rossby waves and their interactions with differential rotation and spot-producing magnetic fields, reveal the opportunity to simulate and predict the occurrence, strength and location of enhanced activity bursts a few weeks up to several months in advance. We now have a golden opportunity to fill in this gap in time-scales of forecasting space weather. This requires a) continuous observations of solar Rossby waves by various techniques; b) development of coupled nonlinear MHD models that simulate both global Rossby waves and the much smaller spatial scale emergence of new active regions; c) application of advanced data assimilation techniques to couple surface observations to update the model-system to integrate forward in time for creating forecasts months ahead. Then it will be possible to build operational prediction models to meet the needs of customers and stakeholders, including support of future NASA missions, regarding what kind and level of space weather to expect a few weeks to several months ahead.

SMD↗